Principal Distributed Systems Engineer

Principal Distributed Systems Engineer at IonQ, Santa Clara, California, United States. A lead-level full time position in the Quantum Platform - Network & Security team, listed under software engineering. About IonQ: IonQ, Inc . [NYSE: IONQ] is the world’s leading quantum platform and merchant supplier - delivering integrated quantum solutions across computing, networking, sensing, and security. IonQ’s newest generation of quantum computers, the IonQ Tempo, is the latest in a line of cutting‑edge systems that have been helping customers and partners including Amazon Web Services, and AstraZeneca achieve 20x performance results and accelerate innovation in drug discovery, materials science, financial modeling, logistics, cybersecurity, and defense. In 2025, the company achieved 99.99% two‑qubit gate fidelity, setting a world record in quantum computing performance . Headquartered in College Park, Maryland, IonQ has operations in California, Colorado, Massachusetts, Tennessee, Washington, Italy, South Korea, Sweden, Switzerland, Canada, and the United Kingdom. Our quantum computing services are available through all major cloud providers, while we also meet the needs of networking and sensing customers across land, sea, air, and space. IonQ is making quantum platforms more accessible and impactful than ever before. Location: This role is based onsite at our office in Santa Clara, CA. Travel: Up to 15%, domestic or international. The Role: We are looking for a Principal Distributed Systems Engineer to join the team building IonQ's Network and Security Platform. As a Principal Distributed Systems Engineer, you’ll be part of a cross‑functional team whose mission is to lead IonQ on its journey to build the world’s best quantum computers to solve the world’s most complex problems — and to secure the world’s networks against quantum threats. In this role, you will be responsible for setting the technical direction and end‑to‑end architecture of the platform's distributed backend — the ingestion pipelines, event streaming and telemetry processing, time‑series and data storage layers, and APIs that give operators real‑time visibility into their networks and the in Requirements

15+ years of software engineering experience building and operating distributed backend systems and platforms at scale, or an equivalent combination of education and experience. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Demonstrated record as a hands‑on architect: defining the architecture and multi‑year roadmap for large‑scale distributed platforms and driving them through to production. Deep experience designing distributed data systems: event streaming (Kafka, Kinesis, or equivalent), high‑throughput ingestion pipelines, and time‑series or large‑scale data stores. Strong fundamentals in distributed systems: consistency models, failure modes, backpressure, idempotency, and exactly‑once vs. at‑least‑once processing tradeoffs. Hands‑on proficiency in at least one production systems language (Go, Rust, Java, or Scala), with the ability to build reference implementations and review production code. Extensive experience with cloud‑native architecture on AWS (GCP or Azure a plus): containerization, Kubernetes, infrastructure‑as‑code, security, and cost optimization. Experience designing multi‑tenant platforms with strong data isolation, access control, and governance. Nice to Have

Master's degree in Computer Science, Engineering, or a related discipline. Production experience in Go and/or Rust. Experience with network telemetry and network management platforms — gNMI/gRPC, NETCONF, SNMP, YANG data models — or prior work at a network equipment vendor or network management company (e.g., Juniper, Cisco, Arista, Nokia). Experience with graph databases or graph data models for network topology (e.g., Neo4j, Amazon Neptune, or custom adjacency representations). Experience with AI/ML platform infrastructure (MLOps / LLMOps, model governance, agentic workflows) applied to operational or network data. Experience in regulated, security-conscious environments (FedRAMP, NIST, or equivalent).

#J-18808-Ljbffr